F. Curie

Elemental properties, hydrology, and biology interact to shape concentration‐discharge curves for carbon, nutrients, sediment, and major ions

To investigate the prevalence and cause of concentration-discharge (C-Q) relationships for carbon, nutrients, major ions, and particulates, we analyzed 40 years of water quality data from 293 monitoring stations in France. Catchments drained diverse landscapes and ranged from 50 to 110,000 km2, together covering nearly half of France. To test for differences during low and high flows, we calculated independent C-Q slopes above and below the median discharge. We found that 84% of all catchment-element combinations were chemodynamic for at least half of the hydrograph and 60% of combinations showed non-linear C-Q curves. Only two or three of the nine possible C-Q modalities were manifest for each parameter, and these modalities were stable through time, suggesting that intrinsic and extrinsic elemental properties (e.g. solubility, reactivity, and source dynamics) set basic C-Q templates for each parameter, which are secondarily influenced by biological activity during low flows, and the interaction between hydrology and catchment characteristics at high flows. Several patterns challenged current C-Q views, including low-flow chemostasis for TSS in 66% of catchments, low-flow biological mediation of NO3- in 71% of catchments, and positive C-Q for dissolved organic carbon independent of catchment size in 80% of catchments. Efforts to reduce nutrient loading decreased phosphorus concentration and altered C-Q curves, but NO3- continued to increase. While C-Q segmentation requires more data than a single analysis, the prevalence of non-linear C-Q slopes demonstrates the potential information loss associated with linear or monotonic analysis of C-Q relationships, and conversely, the value of long-term monitoring. This article is protected by copyright. All rights reserved.

Assessing N emissions in surface water at the national level: comparison of country-wide vs. regionalized models.

Many countries are developing models to estimate N emissions in rivers as part of national-scale water quality assessments. Generally, models are applied with national databases, while at the regional scale, more detailed databases are sometimes available. This paper discusses pros and cons of developing regionalized models versus applying countrywide models. A case study is used to support the discussion. The model used, called Nutting-N (NUTrient Transfer modelING-Nitrogen), relies on a statistical approach linking nitrogen sources and watershed land and river characteristics and aims to evaluate the risk of water bodies failing to reach quality objectives defined by national and federal policies. After calibration and evaluation at the national scale (France), the predictive quality of the model was compared with two regionalized models in a crystalline massif (Brittany, western France, 27,000 km(2)) and in a sedimentary basin (Seine, Paris basin, 78,000 km(2)), where detailed regional databases are available. The national-scale model provided robust predictions in most conditions encountered in France (efficiency=0.69). Terrestrial retention was related mainly to specific runoff, and its median value was estimated at 49% of the N surplus, whereas median river retention represented 18% of incoming N discharge. Regionalizing the model generally improved goodness-of-fit, as the root mean squared error was reduced by 6-24%. However, precision of parameter estimates degraded when too few monitoring basins were available or when variability in land and river characteristics was too low in the calibration dataset. Hence, regional-scale models should be advocated only after the trade-off between improvement of fit and degradation of parameter estimates is examined.

Transferring measured discharge time series: Large-scale comparison of Top-kriging to geomorphology-based inverse modeling

Few methods directly transfer streamflow measurements for continuous prediction of ungauged catchments. Top-kriging has been used mainly to predict the statistical properties of runoff, but has been shown to outperform traditional regionalization approaches of rainfall-runoff models. We applied the Top-kriging approach across the Loire river basin and compared predictions to a geomorphology-based approach. Whereas Top-kriging uses spatial correlation, the other approach has the advantage of being more physically-based by using a well-known geomorphology-based hydrological model (WFIUH) and its inversion. Both approaches require an equal degree of calibration and provide similar performances. We also demonstrate that the Ghosh distance, which considers the nested nature of catchments, can be used efficiently to calculate weights and to identify the suitability of gauged catchments for use as donor catchments. This result is particularly relevant for catchments with Strahler orders above five, i.e., where donor catchments are more strongly nested. This article is protected by copyright. All rights reserved.